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How do we manage increasing complexity and limited attention span in Agile Supply Chains?
Supply Chain managers face a dilemma. They need to go more granular with more demand drivers for better Demand Sensing, increasing the complexity of evolving patterns and computing. At the same time, their team’s attention span is limited. How do we manage this dilemma?
As regards Demand Sensing, increased complexity should be managed through self-learning AI/ML models to decipher the demand patterns at the granular level. Human intervention should be limited in running these models, so that we can run them at higher frequency. Daily run is becoming the norm in FMCG companies and hourly runs in Quick Commerce.
Teams should manage their limited attention span only on exceptions and improvements. Oversight of Demand Sensing models should be limited to those sku-node combinations where prediction errors are either high or increasing… the models possibly need intervention in fine tuning.
Supply actions should be in auto mode on replenishment, with team’s attention required only in exception handling. Improvements in flow and agility should be focused on the constraint and bottlenecks.
Teams using these guidelines are able to improve their Supply Chain agility continually and substantially.